Comparative analysis of weighted gene co-expression networks in human and mouse.

ABSTRACT: The application of complex network modeling to analyze large co-expression data sets has gained traction during the last decade. In particular, the use of the weighted gene co-expression network analysis framework has allowed an unbiased and systems-level investigation of genotype-phenotype relationships in a wide range of systems. Since mouse is an important model organism for biomedical research on human disease, it is of great interest to identify similarities and differences in the functional roles of human and mouse orthologous genes. Here, we develop a novel network comparison approach which we demonstrate by comparing two gene-expression data sets from a large number of human and mouse tissues. The method uses weighted topological overlap alongside the recently developed network-dec

SUBMITTER: Eidsaa M 

PROVIDER: S-EPMC5697817 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature